气候变化模型多模型集合的新方法:关于自然变异性与历史和未来气候代表性的观点

IF 6.1 1区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Yong-Tak Kim , Jae-Ung Yu , Tae-Woong Kim , Hyun-Han Kwon
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引用次数: 0

摘要

本研究开发了一种新方法,将气候模式选择和多模式集合(MME)构建结合起来,以有效表示模式的不确定性,从而提高不同情景下极端降雨量变化评估的一致性。我们的重点是将 10 个区域气候模式(RCM)模拟结果与两个全球气候模式(GCM)模拟结果结合起来,特别是用于估算气候变化下的设计降雨量。我们假设,在来自 RCM 的极端降雨模拟中,自然变异性和统计上更高的矩属性并未完全保留。因此,MME 方法在气候变化研究中可能更加有效,这主要是由于使用了多种气候模型。首先,提出了一项实验研究,以验证所提议的建模框架方法的有效性,该方法采用 L 矩来量化气候模式之间的相对重要性,并在 MME 构建中用于表示自然变异性。然后,将所提出的方法应用于从多个区域气候模型中收集的汉江流域历史(1981-2005 年)和未来(2006-2 100 年)期间的气候变化情景。结果表明,以自然变率为依据的气候模式选择表现较好,与汉江流域观测到的年最大降雨量(AMR)分布几乎一致。与所有情景相比,所选情景的范围相对较窄,且变化率与有限的零点跨越更加一致,这分别反映了模型性能和历史及未来时段一致性的改善。在 RCP8.5 条件下,近未来(2011-2040 年)和远未来(2071-2 100 年)的 MME 变化率增加了约 20%,中未来(2041-2070 年)的 MME 变化率增加程度略低于其他时期,增加了约 10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel approach to a multi-model ensemble for climate change models: Perspectives on the representation of natural variability and historical and future climate

This study developed a novel approach that integrated climate model selection and multi-model ensemble (MME) construction to effectively represent model uncertainties and, consequently, improve consistency in the evaluation of changes to extreme rainfall in different scenarios. Our focus was to combine 10 regional climate model (RCM) simulations, forced by two global climate models (GCM), especially for estimation of design rainfall in a changing climate. We hypothesized that the natural variability and statistically higher moment attributes in the extreme rainfall simulations from RCMs were not fully preserved. Therefore, the MME approach could be more effective in climate change studies, largely due to the use of multiple climate models. First, an experimental study was proposed to validate the efficacy of the proposed modeling framework approach adopting L-moments to quantify relative importance among climate models and their use for representing natural variability in the MME construction. The proposed approach was then applied to climate change scenarios collected from multiple RCMs for the Han-River watershed during both historical (1981–2005) and future (2006–2 100) periods. The results showed that the climate model selection informed by natural variability demonstrated better performance, representing nearly identical distribution to the observed annual maximum rainfall (AMR) in the Han River watershed. The range of the selected scenario was relatively narrower than that of all the scenarios, and the change rate was more consistent with the limited zero crossing, reflecting improvement in both model performance and consistency over historical and future periods, respectively. The change rate of the MME under RCP8.5 appeared to be an approximately 20% increase for the near (2011–2040) and far (2071–2 100) future, and the degree of increase in the rate for the mid-future (2041–2070) was slightly lower than that for the other periods, with increase of approximately 10%.

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来源期刊
Weather and Climate Extremes
Weather and Climate Extremes Earth and Planetary Sciences-Atmospheric Science
CiteScore
11.00
自引率
7.50%
发文量
102
审稿时长
33 weeks
期刊介绍: Weather and Climate Extremes Target Audience: Academics Decision makers International development agencies Non-governmental organizations (NGOs) Civil society Focus Areas: Research in weather and climate extremes Monitoring and early warning systems Assessment of vulnerability and impacts Developing and implementing intervention policies Effective risk management and adaptation practices Engagement of local communities in adopting coping strategies Information and communication strategies tailored to local and regional needs and circumstances
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